Difference between data type 'datetime64[ns]' and '<M8[ns]'?

Question

I have created a TimeSeries in pandas:

In [346]: from datetime import datetime

In [347]: dates = [datetime(2011, 1, 2), datetime(2011, 1, 5), datetime(2011,         


        

Answer 1

datetime64[ns] is a general dtype, while <M8[ns] is a specific dtype. General dtypes map to specific dtypes, but may be different from one installation of NumPy to the next.

On a machine whose byte order is little endian, there is no difference between np.dtype('datetime64[ns]') and np.dtype('<M8[ns]'):

In [6]: np.dtype('datetime64[ns]') == np.dtype('<M8[ns]')
Out[6]: True

However, on a big endian machine, np.dtype('datetime64[ns]') would equal np.dtype('>M8[ns]').

So datetime64[ns] maps to either <M8[ns] or >M8[ns] depending on the endian-ness of the machine.

There are many other similar examples of general dtypes mapping to specific dtypes: int64 maps to <i8 or >i8, and int maps to either int32 or int64 depending on the bit architecture of the OS and how NumPy was compiled.

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Apparently, the repr of the datetime64 dtype has change since the time the book was written to show the endian-ness of the dtype.

Answer 2

If this is generating errors in running your code, upgrading pandas and numpy synchronously is likely to solve the conflict in datetime datatype.